Semantic segmentation assigns semantic labels to at least some pixels, and typically to all pixels, of an image. Meanwhile, instance segmentation seeks to assign instance-wise labels to the image, which involves a combination of semantic segmentation and object detection.
Conventional convolutional neural networks perform either semantic segmentation or instance segmentation, but not both. Some research regarding convolutional neural networks has proposed multi-task segmentation networks that perform both semantic and instance segmentation. However, training a multi-task convolutional neural network is difficult to optimize.
Therefore, it would be advantageous if one or more new or improved multi-task convolutional neural networks along with new or improved training method could be developed that largely or entirely overcame one or more of the aforementioned limitations associated with conventional multi-task convolutional neural networks, and/or avoided or overcame one or more other disadvantages, and/or provided one or more other advantages.